Beyond supervised learning in remote sensing: A systematic review of deep learning approaches
An increasing availability of remote sensing data in the era of geo big-data makes producing
well-represented, reliable training data to be more challenging and requires an excessive …
well-represented, reliable training data to be more challenging and requires an excessive …
Remote sensing image classification using an ensemble framework without multiple classifiers
Recently, ensemble multiple deep learning (DL) classifiers has been reported to be an
effective method for improving remote sensing classification accuracy. Although these …
effective method for improving remote sensing classification accuracy. Although these …
Predictive performance of machine learning model with varying sampling designs, sample sizes, and spatial extents
Using machine learning and earth observation data to capture real-world variability in
spatial predictive mapping depends on sample size, design, and spatial extent …
spatial predictive mapping depends on sample size, design, and spatial extent …
Mapping lulc dynamics and its potential implication on forest cover in malam jabba region with landsat time series imagery and random forest classification
M Junaid, J Sun, A Iqbal, M Sohail, S Zafar, A Khan - Sustainability, 2023 - mdpi.com
Pakistan has an annual deforestation rate of 4.6% which is the second highest in Asia. It has
been described by the Food and Agriculture Organization (FAO) that the deforestation rate …
been described by the Food and Agriculture Organization (FAO) that the deforestation rate …
[HTML][HTML] Analysis and prediction of the impact of land use/cover change on ecosystem services value in Gansu province, China
Z Yin, Q Feng, R Zhu, L Wang, Z Chen, C Fang… - Ecological Indicators, 2023 - Elsevier
The effects of land use/cover change (LUCC) on the spatial distribution and change of
ecosystem service value (ESV) are still ambiguous, and cannot effectively guide the …
ecosystem service value (ESV) are still ambiguous, and cannot effectively guide the …
Improving crop classification accuracy with integrated Sentinel-1 and Sentinel-2 data: a case study of barley and wheat
Crop classification plays a crucial role in ensuring food security, agricultural policy
development, and effective land management. Remote sensing data, particularly Sentinel-1 …
development, and effective land management. Remote sensing data, particularly Sentinel-1 …
Drought-related spatiotemporal cumulative and time-lag effects on terrestrial vegetation across China
Vegetation is one of the most important indicators of climate change, as it can show regional
change in the environment. Vegetation health is affected by various factors, including …
change in the environment. Vegetation health is affected by various factors, including …
Effects of 2D/3D urban morphology on land surface temperature: Contribution, response, and interaction
B Yuan, L Zhou, F Hu, C Wei - Urban Climate, 2024 - Elsevier
Urban morphology severely affects the intra-urban heat flux transport and thus directly
regulates urban thermal environment. Despite previous studies suggested that urban …
regulates urban thermal environment. Despite previous studies suggested that urban …
Machine learning-based global air quality index development using remote sensing and ground-based stations
Air pollution refers to the presence of hazardous substances in the air that has adverse
effects on health, causing millions premature deaths annually. Ground-based stations can …
effects on health, causing millions premature deaths annually. Ground-based stations can …
An improved faster R-CNN method for landslide detection in remote sensing images
H Qin, J Wang, X Mao, Z Zhao, X Gao, W Lu - Journal of Geovisualization …, 2024 - Springer
Landslides are the most common type of geological disaster in China, causing substantial
property losses and casualties. It is of great significance for disaster prevention and …
property losses and casualties. It is of great significance for disaster prevention and …